Spectral analysis is a key tool for identifying periodic patterns in sedimentary sequences, including astronomically related orbital signals. While most spectral analysis methods require equally spaced samples, this condition is rarely achieved either in the field or when sampling sediment core. Here, we propose a method to assess the impact of the uncertainty or error made in the measurement of the sample stratigraphic position on the resulting power spectra. We apply a Monte Carlo procedure to randomise the sample steps of depth series using a gamma distribution. Such a distribution preserves the stratigraphic order of samples and allows controlling the average and the variance of the distribution of sample distances after randomisation. We apply the Monte Carlo procedure on two geological datasets and find that gamma distribution of sample distances completely smooths the spectrum at high frequencies and decreases the power and significance levels of the spectral peaks in an important proportion of the spectrum. At 5 % of stratigraphic uncertainty, a small portion of the spectrum is completely smoothed. Taking at least three samples per thinnest cycle of interest should allow this cycle to be still observed in the spectrum, while taking at least four samples per thinnest cycle of interest should allow its significance levels to be preserved in the spectrum. At 10 and 15 % uncertainty, these thresholds increase, and taking at least four samples per thinnest cycle of interest should allow the targeted cycles to be still observed in the spectrum. In addition, taking at least 10 samples per thinnest cycle of interest should allow their significance levels to be preserved. For robust applications of the power spectrum in further studies, we suggest providing a strong control of the measurement of the sample position. A density of 10 samples per putative precession cycle is a safe sampling density for preserving spectral power and significance level in the Milankovitch band. For lower sampling density, the use of gamma-law simulations should help in assessing the impact of stratigraphic uncertainty in the power spectrum in the Milankovitch band. Gamma-law simulations can also model the distortions of the Milankovitch record in sedimentary series due to variations in the sedimentation rate. [less ▲]

Trends in the atmospheric concentration of CO2 during three recent interglacials, the Holocene, the Eemian and Marine Isotope Stage (MIS) 11, are investigated using an Earth system Model of Intermediate ... [more ▼]

Trends in the atmospheric concentration of CO2 during three recent interglacials, the Holocene, the Eemian and Marine Isotope Stage (MIS) 11, are investigated using an Earth system Model of Intermediate Complexity, which we extended with modules to dynamically determine two slow carbon cycle processes – peat accumulation and shallow-water CaCO3 sedimentation (coral reef formation). For all three interglacials, model simulations considering peat accumulation and shallow water CaCO3 sedimentation substantially improve the agreement between model results and ice core CO2 reconstructions in comparison to a carbon cycle setup neglecting these processes. This enables us to model the trends in atmospheric CO2, with modelled trends similar to the ice core data, forcing the model only with orbital and sea level changes. During the Holocene, anthropogenic CO2 emissions are required to match the observed rise in atmospheric CO2 after 3 ka BP, but are not relevant before this time. Therefore our model experiments show for the first time how the CO2 evolution during the Holocene and two recent interglacials can be explained consistently using an identical model setup. [less ▲]

A tree-ring analysis based on oak samples in the North-West of France showed the effects of droughts periods on the growth index, during the late XIXth and XXth century. Four types of droughts were ... [more ▼]

A tree-ring analysis based on oak samples in the North-West of France showed the effects of droughts periods on the growth index, during the late XIXth and XXth century. Four types of droughts were identified using the results of the tree-ring analysis and the available climate data. The “type 1” was subjected to a continuous and intense drought during all the vegetative period (spring and summer), the “type 2” was subjected to a summer drought succeeding no precipitation deficit in spring, the “type 3” was subjected to a remarkable winter drought and during the years of the “type 4”, precipitation deficits were recorded for several but not successive months, over an heterogeneous spatial distribution. The long, intense and countinuous droughts clearly showed a spatial structuring effect on the growth index, especially when the two successive vegetative seasons (spring and summer) recorded strong precipitation deficits combined with shrivellings. These extreme cases involved the lowest growth index over most of the studied area, with some variations due to the altitude and exposure effects on the local-scale spatial distribution of the hydrological stress. The hydrological balance for the station of Rennes (Brittany) confirmed these results in accordance with the intensity and/or duration of drought periods: the most intense droughts of the “type 1“ were especially pointed out. A climatic interpretation of growth index data and maps could so be possible over northwestern France with an application to the medieval times and perhaps to other periods, but the cause of the different drought patterns must be more precisely studied during the contemporary period (late XIXth century and all the XXth century). [less ▲]

The paper “Application of sediment core modelling to understanding climates of the past: An example from glacial-interglacial changes in Southern Oceansilica cycling” by A. Ridgwell is reviewed and ... [more ▼]

The paper “Application of sediment core modelling to understanding climates of the past: An example from glacial-interglacial changes in Southern Oceansilica cycling” by A. Ridgwell is reviewed and comented. [less ▲]